Multi-sensor data fusion for underwater archaeological investigation

The primary purpose of this work consists in treating optical and acoustic signals in order to extract useful information for applications in underwater archaeology. Data are processed to assess the presence of geometrically regular elements, potentially indicating handmade objects lying on the seafloor. Geometrical elements are recognized by means of suitable algorithms and their statistical persistence in the data stream is employed as a descriptor. Multi-sensor data are processed by applying segmentation and classification procedures based on a geometrical pattern analysis, with the purpose of discerning different materials. We basically seek for meaningful features in the data in order to perform robust object recognition, also in case of unfavorable environmental conditions. Finally we define a unique data fusion model that can be exploited for exhaustive interpretation of the underwater scene.